Combination of CE-MS and advanced chemometric methods for high-throughput metabolic profiling.

In this work, an untargeted approach based on capillary electrophoresis-mass spectrometry (CE-MS) in combination with multivariate data analyses is proposed as a high-throughput general methodology for metabolomic studies. First, total ion electropherograms (TIEs) were considered for exploratory and classification purposes by means of principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Then, multivariate curve resolution alternating least squares (MCR-ALS) was applied to the multiple full scan MS data sets. This strategy permitted the resolution of a large number of metabolites being characterized by their electrophoretic peaks and their corresponding mass spectra. The proposed approach allowed solving additional electrophoretic issues, such as background noise contributions, low signal-to-noise ratios, asymmetric peaks and migration time shifts. The usefulness of the proposed methodology is demonstrated in a comparative study of the metabolic profiles from baker's yeast (Saccharomyces cerevisiae) samples cultured at two temperatures, 30°C and 37°C. A total number of 80 metabolites were relevant to yeast samples differentiation at the two temperatures and almost 50 of them were tentatively identified based on their accurate experimental molecular mass. The results show that changes in amino acid, nucleotide and lipid metabolic pathways participated in the acclimatization of yeast cells to grow at 37°C.

Assessment of endocrine disruptors effects on zebrafish (Danio rerio) embryos by untargeted LC-HRMS metabolomic analysis.

Bisphenol A (BPA), perfluorooctane sulfonate (PFOS), and tributyltin (TBT) are emerging endocrine disruptors (EDCs) with still poorly defined mechanisms of toxicity and metabolic effects in aquatic organisms. We used an untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) metabolomic approach to study the effects of sub-lethal doses of these three EDCs on the metabolic profiles of zebrafish embryos exposed from 48 to 120hpf (hours post fertilization). Advanced chemometric data analysis methods were used to reveal effects on the subjacent regulatory pathways. EDC treatments induced changes in concentrations of about 50 metabolites for TBT and BPA, and of 25 metabolites for PFOS. The analysis of the corresponding metabolic changes suggested the presence of similar underlying zebrafish responses to BPA, TBT and PFOS affecting the metabolism of glycerophospholipids, amino acids, purines and 2-oxocarboxylic acids. We related the changes in glycerophospholipid metabolism to alterations in absorption of the yolk sack, the main source of nutrients (including lipids) for the developing embryo, linking the molecular markers with adverse phenotypic effects. We propose a general mode of action for all three chemical compounds, probably related to their already described interaction with the PPAR/RXR complex, combined with specific effects on different signaling pathways resulting in particular alterations in the zebrafish embryos metabolism.

Dose-dependent transcriptomic responses of zebrafish eleutheroembryos to Bisphenol A.

Despite the abundant literature on the adverse effects of Bisphenol A (BPA) as endocrine disruptor, its toxicity mechanisms are still poorly understood. We present here a study of its effects on the zebrafish eleutheroembryo transcriptome at concentrations ranging from 0.1 to 4 mg L-1, this latter representing the lowest observed effect concentration (LOEC) found in our study at three different macroscopical endpoints (survival, hatching and swim bladder inflation). Multivariate data analysis methods identified both monotonic and bi-phasic patterns of dose-dependent responses. Functional analyses of genes affected by BPA exposure suggest an interaction of BPA with different signaling pathways, being the estrogenic and retinoid receptors two likely targets. In addition, we identified an apparently unrelated inhibitory effect on, among others, visual function genes. We interpret our data as the result of a sum of underlying, independent molecular mechanisms occurring simultaneously at the exposed animals, well below the macroscopic LOEC, but related to at least some of the observed morphological alterations, particularly in eye size and yolk sac resorption. Our data supports the idea that the physiological effects of BPA cannot be only explained by its rather weak interaction with the estrogen receptor, and that multivariate analyses are required to analyze the effects of toxicants like BPA, which interact with different cellular targets producing complex phenotypes.

Modelling of Hydrophilic Interaction Liquid Chromatography Stationary Phases Using Chemometric Approaches.

Metabolomics is a powerful and widely used approach that aims to screen endogenous small molecules (metabolites) of different families present in biological samples. The large variety of compounds to be determined and their wide diversity of physical and chemical properties have promoted the development of different types of hydrophilic interaction liquid chromatography (HILIC) stationary phases. However, the selection of the most suitable HILIC stationary phase is not straightforward. In this work, four different HILIC stationary phases have been compared to evaluate their potential application for the analysis of a complex mixture of metabolites, a situation similar to that found in non-targeted metabolomics studies. The obtained chromatographic data were analyzed by different chemometric methods to explore the behavior of the considered stationary phases. ANOVA-simultaneous component analysis (ASCA), principal component analysis (PCA) and partial least squares regression (PLS) were used to explore the experimental factors affecting the stationary phase performance, the main similarities and differences among chromatographic conditions used (stationary phase and pH) and the molecular descriptors most useful to understand the behavior of each stationary phase.

Metabolic disruption of zebrafish (Danio rerio) embryos by bisphenol A. An integrated metabolomic and transcriptomic approach.

Although bisphenol A (BPA) is commonly recognized as an endocrine disruptor, the metabolic consequences of its exposure are still poorly understood. In this study, we present a non-targeted LC-MS based metabolomic analysis in combination with a full-genome, high-throughput RNA sequencing (RNA-Seq) to reveal the metabolic effects and the subjacent regulatory pathways of exposing zebrafish embryos to BPA during the first 120 hours post-fertilization. We applied multivariate data analysis methods to extract biochemical information from the LC-MS and RNA-Seq complex datasets and to perform testable predictions of the phenotypic adverse effects. Metabolomic and transcriptomic data revealed a similar subset of altered pathways, despite the large difference in the number of identified biomarkers (around 50 metabolites and more than 1000 genes). These results suggest that even a moderate coverage of zebrafish metabolome may be representative of the global metabolic changes. These multi-omic responses indicate a specific metabolic disruption by BPA affecting different signaling pathways, such as retinoid and prostaglandin metabolism. The combination of transcriptomic and metabolomic data allowed a dynamic interpretation of the results that could not be drawn from either single dataset. These results illustrate the utility of -omic integrative analyses for characterizing the physiological effects of toxicants beyond the mere indication of the affected pathways.

Knowledge integration strategies for untargeted metabolomics based on MCR-ALS analysis of CE-MS and LC-MS data.

In this work, two knowledge integration strategies based on multivariate curve resolution alternating least squares (MCR-ALS) were used for the simultaneous analysis of data from two metabolomic platforms. The benefits and the suitability of these integration strategies were demonstrated in a comparative study of the metabolite profiles from yeast (Saccharomyces cerevisiae) samples grown in non-fermentable (acetate) and fermentable (glucose) carbon source. Untargeted metabolomics data acquired by capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC-MS) were jointly analysed. On the one hand, features obtained by independent MCR-ALS analysis of each dataset were joined to obtain a biological interpretation based on the combined metabolic network visualization. On the other hand, taking advantage of the common spectral mode, a low-level data fusion strategy was proposed merging CE-MS and LC-MS data before the MCR-ALS analysis to extract the most relevant features for further biological interpretation. Then, results obtained by the two presented methods were compared. Overall, the study highlights the ability of MCR-ALS to be used in any of both knowledge integration strategies for untargeted metabolomics. Furthermore, enhanced metabolite identification and differential carbon source response detection were achieved when considering a combination of LC-MS and CE-MS based platforms.

Preparation and evaluation of open tubular C18-silica monolithic microcartridges for preconcentration of peptides by on-line solid phase extraction capillary electrophoresis.

In this study, C18-silica monoliths were synthesized as a porous layer in open tubular capillary columns, to be cut later into microcartridges for the analysis of neuropeptides by on-line solid-phase extraction capillary electrophoresis with UV and MS detection (SPE-CE-UV and SPE-CE-MS). First, several types of C18-silica monolithic (MtC18) microcartridges were used to analyse standard solutions of five neuropeptides (i.e. dynorphin A (1-7), substance P (7-11), endomorphin 1, methionine enkephalin and [Ala]-methionine enkephalin). The MtC18 sorbents were especially selective against endomorphin 1 and substance P (7-11)). The best results in terms of sensitivity and inter-microcartridge reproducibility were achieved with the microcartridges obtained from a 10-cm open tubular capillary column with a thin monolithic coating with large through-pores (1-5µm). Run-to-run repeatability, microcartridge durability, linearity ranges and LODs were studied by MtC18-SPE-CE-MS. As expected due to their greater selectivity, the best LOD enhancement was obtained for End1 and SP (7-11) (50 times with regard to CE-MS). Finally, the suitability of the methodology for analysing biological fluids was tested with plasma samples spiked with End1 and SP (7-11). Results obtained were promising because both neuropeptides could be detected at 0.05µgmL(-1), which was almost the same concentration level as for the standard solutions (0.01µgmL(-1)).